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You searched for +publisher:"University of New Orleans" +contributor:("Steve Rick"). One record found.

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1. Maus, Aaron. Formulation of Hybrid Knowledge-Based/Molecular Mechanics Potentials for Protein Structure Refinement and a Novel Graph Theoretical Protein Structure Comparison and Analysis Technique.

Degree: PhD, Computer Science, 2019, University of New Orleans

Proteins are the fundamental machinery that enables the functions of life. It is critical to understand them not just for basic biology, but also to enable medical advances. The field of protein structure prediction is concerned with developing computational techniques to predict protein structure and function from a protein’s amino acid sequence, encoded for directly in DNA, alone. Despite much progress since the first computational models in the late 1960’s, techniques for the prediction of protein structure still cannot reliably produce structures of high enough accuracy to enable desired applications such as rational drug design. Protein structure refinement is the process of modifying a predicted model of a protein to bring it closer to its native state. In this dissertation a protein structure refinement technique, that of potential energy minimization using hybrid molecular mechanics/knowledge based potential energy functions is examined in detail. The generation of the knowledge-based component is critically analyzed, and in the end, a potential that is a modest improvement over the original is presented. This dissertation also examines the task of protein structure comparison. In evaluating various protein structure prediction techniques, it is crucial to be able to compare produced models against known structures to understand how well the technique performs. A novel technique is proposed that allows an in-depth yet intuitive evaluation of the local similarities between protein structures. Based on a graph analysis of pairwise atomic distance similarities, multiple regions of structural similarity can be identified between structures independently of relative orientation. Multidomain structures can be evaluated and this technique can be combined with global measures of similarity such as the global distance test. This method of comparison is expected to have broad applications in rational drug design, the evolutionary study of protein structures, and in the analysis of the protein structure prediction effort. Advisors/Committee Members: Christopher Summa, MD Tamjidul Hoque, Steve Rick.

Subjects/Keywords: Bioinformatics; Protein Structure Prediction; Protein Structure Refinement; Statistical Energy Functions; Protein Structure Comparison; Graph Analysis; Bioinformatics

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Maus, A. (2019). Formulation of Hybrid Knowledge-Based/Molecular Mechanics Potentials for Protein Structure Refinement and a Novel Graph Theoretical Protein Structure Comparison and Analysis Technique. (Doctoral Dissertation). University of New Orleans. Retrieved from https://scholarworks.uno.edu/td/2673

Chicago Manual of Style (16th Edition):

Maus, Aaron. “Formulation of Hybrid Knowledge-Based/Molecular Mechanics Potentials for Protein Structure Refinement and a Novel Graph Theoretical Protein Structure Comparison and Analysis Technique.” 2019. Doctoral Dissertation, University of New Orleans. Accessed January 18, 2020. https://scholarworks.uno.edu/td/2673.

MLA Handbook (7th Edition):

Maus, Aaron. “Formulation of Hybrid Knowledge-Based/Molecular Mechanics Potentials for Protein Structure Refinement and a Novel Graph Theoretical Protein Structure Comparison and Analysis Technique.” 2019. Web. 18 Jan 2020.

Vancouver:

Maus A. Formulation of Hybrid Knowledge-Based/Molecular Mechanics Potentials for Protein Structure Refinement and a Novel Graph Theoretical Protein Structure Comparison and Analysis Technique. [Internet] [Doctoral dissertation]. University of New Orleans; 2019. [cited 2020 Jan 18]. Available from: https://scholarworks.uno.edu/td/2673.

Council of Science Editors:

Maus A. Formulation of Hybrid Knowledge-Based/Molecular Mechanics Potentials for Protein Structure Refinement and a Novel Graph Theoretical Protein Structure Comparison and Analysis Technique. [Doctoral Dissertation]. University of New Orleans; 2019. Available from: https://scholarworks.uno.edu/td/2673

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